Teradata is evolving its Tera platform, transforming it into an agentic coworker for enterprise data work to deliver outcomes.
Through natural language and guided execution, everyone from business analysts to platform engineers and database administrators can analyze data, build AI applications, operate infrastructure, and automate complex workflows—all from a single governed environment that reaches enterprise data across platforms, not just within Teradata, according to the company.
Tera includes three key capabilities:
- Tera Context Engine, a vendor-neutral context and orchestration layer that gives AI governed business knowledge.
- Tera Harness, an intelligent execution layer that routes work across the right skills, tools, data, and models.
- Agent Skills, purpose-built for data engineering, data analysis, and data science.
Tera addresses two requirements enterprise AI has lacked: the ability to understand the business and the ability to act on that understanding, said the vendor.
Teradata customers gain more reliable AI outcomes, better economics from every model interaction, and faster time to value, supported by Teradata AI Services for organizations that want to accelerate deployment.
“Most enterprises are not starting from scratch with AI. They are dealing with tools that do not work together and a skills gap that makes those tools hard to use at scale. Tera is designed to work across that environment, putting business context, intelligent execution, and pre-built expertise into the hands of every person working with data. And equally important is what enterprises do not give up: control over their models, their data, and where everything runs. The result is AI that actually gets work done, at lower cost, with less overhead,” said Sumeet Arora, CPO, Teradata.
Organizations retain the ability to choose which models they use, where workloads run, and how enterprise data is accessed, across cloud, on-premises, and sovereign environments.
Tera executes AI natively within the Teradata environment, including the Teradata Console for database admins, running analytic, and ML workloads directly on enterprise data without external model calls. This eliminates data movement and latency, and reduces hallucination risk for quantitative tasks like forecasting, regression, and segmentation.
For organizations looking to accelerate deployment, Teradata AI Services is designed to help customers avoid the experimentation trap and move directly toward production outcomes, said the vendor.
AI Services helps identify the use cases where governed context will create measurable value, configure Industry Knowledge Models, and get enterprise knowledge into production faster powered by Tera. Teradata’s AI Value Engineering methodology ensures AI programs are designed and developed for production-readiness, not experimentation, and pre-developed agents and tooling built for every stage of the AI development lifecycle accelerate time-to-customer-value, said Teradata.
Tera Context Engine, Tera Harness, and Agent Skills will be available in Q4 2026.
For more information about this news, visit www.teradata.com.